MATLAB Code for Digital Modulation Technique Recognition
MATLAB code for recognizing digital modulation techniques including phase-based and frequency-based methods, featuring implementation details and signal processing algorithms.
Professional MATLAB source code with comprehensive documentation and examples
MATLAB code for recognizing digital modulation techniques including phase-based and frequency-based methods, featuring implementation details and signal processing algorithms.
Linear precoding techniques for MIMO downlink systems based on Zero-Forcing (ZF) and Minimum Mean Square Error (MMSE) criteria with algorithm implementation insights.
COST207.m - MATLAB implementation of COST 207 channel model, GWSSUS.m - Gaussian Wide-Sense Stationary Uncorrelated Scattering model, Technical presentation on Gaussian white noise channel modeling approaches
Regarding simu1: During the initialization process before running Simulink, channel time delay and amplitude estimation is completed. Multipath combining weight coefficients estimation employs optional EG/MR/MMSE combining schemes. Channel options in
This MATLAB simulation demonstrates how the average number of tags per time slot (e) varies with frame size in the Fixed Frame ALOHA anti-collision algorithm for RFID systems, featuring statistical analysis of collision probabilities and throughput o
A MATLAB-based OFDM simulation program featuring QAM modulation for subcarriers with 4 subchannels, implementing signal generation, modulation, and performance analysis.
Determining optical communication outage probability to calculate minimum transmit power under specified bit error rate constraints, including implementation approaches for power optimization algorithms
Implementation of Alamouti coding in STBC-OFDM simulation, including channel encoding/decoding processes and binary source generation with detailed code-level explanations
Implementation of OFDM's autocorrelation cyclic function featuring a 6-path Rayleigh fading channel model with comprehensive delay considerations. The simulation generates cyclic autocorrelation diagrams, cross-sectional plots, and allows customizabl
A comprehensive comparison of multiuser detection algorithms including Decorrelation, MMSE (Minimum Mean Square Error), SIC (Successive Interference Cancellation), and PIC (Parallel Interference Cancellation), featuring implementation approaches and
Simulation implementation and performance analysis of cooperative spectrum sensing in cognitive radio systems, featuring detailed algorithm descriptions and MATLAB-based modeling approaches
EZW MATLAB program featuring comprehensive encoding and decoding modules with detailed algorithm implementation
Complete MATLAB implementations for AM, FM, FSK, GFSK, MSK, and GMSK modulation/demodulation techniques, including voice signal testing capabilities. Each algorithm features detailed code explanations, theoretical analysis, performance comparisons, a
This project provides source code and examples for four clustering algorithms, aiming to develop a standardized and extensible toolkit for clustering tasks. The implementation includes: 1. Clustering algorithms: K-means, K-medoids, FCMclust, GKclust,
A modified MATLAB-based simulation program for MIMO channel capacity analysis, featuring operational code with enhanced parameter customization and performance evaluation capabilities.
The TD-SCDMA rate matching algorithm serves as a valuable reference for beginners studying the TD-SCDMA physical layer, featuring detailed code-level explanations and algorithmic procedures.
This MATLAB program simulates and plots the Bit Error Rate (BER) versus Signal-to-Noise Ratio (SNR) relationship for a 4x4 MIMO-OFDM system implementation, demonstrating key digital communication performance metrics.
Adaptive bit loading and power allocation program for OFDM systems, executed by running OFDM.M to optimize subcarrier allocation and transmission efficiency
Application Context: In LTE communications, MIMO-OFDM technology effectively addresses intra-cell user interference but introduces more severe inter-cell interference. Inter-cell interference significantly limits system capacity and degrades service
A bit error rate simulation for a 2x2 MIMO system employing MMSE-SIC detection at the receiver